A mega-analysis of expression quantitative trait loci (eQTL) provides insight into the regulatory architecture of gene expression variation in liver.
Tobias StrunzFelix GrassmannJavier GayánSatu NahkuriDebora Souza-CostaCyrille MaugeaisSascha FauserEverson NogocekeBernhard Heinrich Friedrich WeberPublished in: Scientific reports (2018)
Genome-wide association studies (GWAS) have identified numerous genetic variants in the human genome associated with diseases and traits. Nevertheless, for most loci the causative variant is still unknown. Expression quantitative trait loci (eQTL) in disease relevant tissues is an excellent approach to correlate genetic association with gene expression. While liver is the primary site of gene transcription for two pathways relevant to age-related macular degeneration (AMD), namely the complement system and cholesterol metabolism, we explored the contribution of AMD associated variants to modulate liver gene expression. We extracted publicly available data and computed the largest eQTL data set for liver tissue to date. Genotypes and expression data from all studies underwent rigorous quality control. Subsequently, Matrix eQTL was used to identify significant local eQTL. In total, liver samples from 588 individuals revealed 202,489 significant eQTL variants affecting 1,959 genes (Q-Value < 0.001). In addition, a further 101 independent eQTL signals were identified in 93 of the 1,959 eQTL genes. Importantly, our results independently reinforce the notion that high density lipoprotein metabolism plays a role in AMD pathogenesis. Taken together, our study generated a first comprehensive map reflecting the genetic regulatory landscape of gene expression in liver.
Keyphrases
- genome wide
- gene expression
- dna methylation
- copy number
- age related macular degeneration
- poor prognosis
- high density
- genome wide association
- big data
- magnetic resonance imaging
- transcription factor
- electronic health record
- quality control
- machine learning
- computed tomography
- binding protein
- single cell
- genome wide association study
- high resolution
- genome wide identification
- low density lipoprotein
- deep learning
- diffusion weighted imaging